c2wind / mapp Goto Github PK
View Code? Open in Web Editor NEWThis project forked from jaijeet/mapp
The Berkeley Model and Algorithm Prototyping Platform
Home Page: https://github.com/jaijeet/MAPP/wiki
License: Other
This project forked from jaijeet/mapp
The Berkeley Model and Algorithm Prototyping Platform
Home Page: https://github.com/jaijeet/MAPP/wiki
License: Other
This is MAPP, the Berkeley Model and Algorithm Prototyping Platform. It includes VAPP (the Berkeley Verilog-A Parser and Processor) organized as a git subtree under the directory VAPP. VAPP has its own README file: VAPP/00-README. Please read that too if you want to use VAPP. Quickstart ------------------------------------------------------------------------------- Note: This "source release" of MAPP (which you have probably obtained via git clone) relies on a UNIX/linux toolchain (it needs, eg, autoconf, make, /bin/bash, a file system that supports soft links, ln -s, etc.). If you are on a non-linux system, the build system probably won't work unless you spend some time tweaking it for your own OS (we cannot do this; please don't ask!). If you cannot use linux or a compatible UNIX-based OS with all the required utilities, you should probably download and use the pre-packaged MAPP tarball available from https://github.com/jaijeet/MAPP/wiki (look near the end of the page), not this "source release" from git. 0. Your having been provided access to MAPP means that you have agreed to abide by the terms of MAPP's license, as laid out in the file 00-LICENSE in this directory. In short, MAPP is released under the GPL-v3, while VAPP is under the LGPL-v3, unless you have a customized license. The 00-LICENSE file contains additional important details; if you have not read it, please do so. VAPP has its own 00-LICENSE file VAPP/00-LICENSE. 1. OPTIONAL: the A2oDAEAPI and A3oDAEAPI submodules of MAPP contain additional analyses (see Setup/installation for more information). A2oDAEAPI and A3oDAEAPI are git repositories in their own right, separate from MAPP. You need to have git to the A2oDAEAPI and A3oDAEAPI repositories. If you do have such access, please set them up as submodules of MAPP, as follows: # in the top-level MAPP directory, ie, where this 0-README file is located git submodule add git@hagrid:A2oDAEAPI.git Analyses2-on-DAEAPI git submodule add git@hagrid:A3oDAEAPI.git Analyses3-on-DAEAPI 2. Setup/installation: $ autoconf $ ./configure # note: the standard arguments --prefix and --exec-prefix # are not used by MAPP at this point. # # The useful optional arguments to configure are: # --with-usercontribs # pull in user contributions to MAPP # # (from the contribs/ directory) # --with-A2oDAEAPI # enable support for additional algorithms # # if you have access to the Analyses2-on-DAEAPI # # submodule (you probably do not, by default). # # If you do, this option provides access to stationary # # LTI noise, parameter sensitivity analysis, harmonic # # balance, shooting, PPV, etc. algorithms. # --with-A3oDAEAPI # enable support for additional algorithms # # if you have access to the Analyses3-on-DAEAPI # # submodule (you probably do not, by default). # # If you do, this option provides access to # # Krylov-subspace based LTI model reduction # # algorithms. # --with-VVimplementation=<vvimpl> # vvimpl = vv1 | vv2 # # VVimplementation selects the implementation of # # automatic differentiation. Once you start MAPP, # # help MAPPautodiff for more information about MAPP's # # automatic differentiation capabilities. # # The default is vv2. Don't change it unless you # # know what you are doing. $ make # this will also "install" The above will create a local installation under ./MAPP-$version/, soft linked to ./MAPP-locallinks-installation for convenience. This "installation" merely sets up soft links to files in your git working copy, so edits to these change the original files. This is convenient for code development. Follow the instructions printed out by make above to ensure that MAPP is set up whenever you start MATLAB. It is best to make clean before make, since the "installation" is non-standard (makes soft links instead of compiling or copying). Some useful make targets are: $ make releasesnapshot # creates a tarball of your installation # under /var/tmp/, suitable for sending # others as a snapshot of the installation. $ make clean # removes the installation $ make autoclean # removes the Makefile. 3. Testing the installation: - Copy or soft link the file start_MAPP.m to ~/Documents/MATLAB/ (or some other directory in MATLAB's default path). - Start MATLAB. Within MATLAB, give the commands: start_MAPP run_BJTdiffpair_DCsweep % a quick test, should produce a tanh() curve MAPPtest_quick MAPPtest % takes about 10m in MATLAB; longer in Octave % MAPPtest('showresults') % to see outputs/plots % the following are not maintained regularly, might throw some errors run_ALL_A1oDAEAPI_tests % this takes a long time run_ALL_A2oDAEAPI_tests % if you have access to the A2oDAEAPI submodule run_ALL_A3oDAEAPI_tests % if you have access to the A3oDAEAPI submodule 4. To clean up the installation (eg, prior to commit/push): $ make clean $ make autoclean 5. Step 3 above does not test A2oDAEAPI or A3oDAEAPI functionalities. Running run_ALL_A2oDAEAPI_tests and run_ALL_A3oDAEAPI_tests will illustrate and test some of this functionality. Warning: these can take a long time to run.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.